Description:
<jats:title>Abstract</jats:title><jats:sec><jats:title>Objective</jats:title><jats:p>To validate imputation methods used to infer plan‐level deductibles and determine which enrollees are in high‐deductible health plans (HDHPs) in administrative claims datasets.</jats:p></jats:sec><jats:sec><jats:title>Data Sources and Study Setting</jats:title><jats:p>2017 medical and pharmaceutical claims from OptumLabs Data Warehouse for US individuals <65 continuously enrolled in an employer‐sponsored plan. Data include enrollee and plan characteristics, deductible spending, plan spending, and actual plan‐level deductibles.</jats:p></jats:sec><jats:sec><jats:title>Study Design</jats:title><jats:p>We impute plan deductibles using four methods: (1) parametric prediction using individual‐level spending; (2) parametric prediction with imputation and plan characteristics; (3) highest plan‐specific mode of individual annual deductible spending; and (4) deductible spending at the 80th percentile among individuals meeting their deductible. We compare deductibles’ levels and categories for imputed versus actual deductibles.</jats:p></jats:sec><jats:sec><jats:title>Data Collection/Extraction Methods</jats:title><jats:p>Not applicable.</jats:p></jats:sec><jats:sec><jats:title>Principal Findings</jats:title><jats:p>All methods had a positive predictive value (PPV) for determining high‐ versus low‐deductible plans of ≥87%; negative predictive values (NPV) were lower. The method imputing plan‐specific deductible spending modes was most accurate and least computationally intensive (PPV: 95%; NPV: 91%). This method also best correlated with actual deductible levels; 69% of imputed deductibles were within $250 of the true deductible.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>In the absence of plan structure data, imputing plan‐specific modes of individual annual deductible spending best correlates with true deductibles and best predicts enrollees in HDHPs.</jats:p></jats:sec>